Libxc is an library for exchange-correlation functions in the density functional theory. This has been developed for the purpose that well-tested exchange-correlation functions can be easily used in any DFT codes. In Libxc, users can find several types of exchange-correlation functions: LDA, GGA, hybrid-GGA, and meta-GGA.
Elastic is a set of python routines for calculation of elastic properties of crystals (elastic constants, equation of state, sound velocities, etc.). It is implemented as a extension to the Atomic Simulation Environment (ASE) system. There is a script providing interface to the library not requiring knowledge of python or ASE system.
Fortran codes for computing the specified k-th eigenvalue and eigenvector for generalized symmetric definite eigenvalue problems. Sylvester’s law of inertia is employed as the fundamental principle in computations, and the sparse direct linear solver (MUMPS) is used in the main routine. By inputting Hamiltonian and its overlap matrices, user can compute electron’s energy and its wave function in the specified k-th energy level.
COMmon Bayesian Optimization Library (COMBO) is an open source python library for machine learning techniques. COMBO is amenable to large scale problems, because the computational time grows only linearly as the number of candidates increases. Hyperparameters of a prediction model can be automatically learned from data by maximizing type-II likelihood.
XenonPy is a high-throughput material exploration framework based on machine learning technologies. This library can generate various chem/phys descriptors for machine learning to explore materials in virtual environment. Descriptors in matminer can be also used. Model training is done by PyTorch. Visualization tool for descriptor and transfer learning framework are also provided.
isqpr is an R package to find candidate molecules that has your desired chemical structures and chemical properties. SMILES (Simplified Molecular Input Line Entry Specification Syntax) is employed to represent chemical structures. To find candidate molecules, sequential Monte Carlo method generates new molecules, whose chemical properties are predicted by machine learning techniques.
i-PI is a universal force engine interface written in Python, designed to be used together with an ab-initio (or force-field based) evaluation of the interactions between the atoms. This application includes a large number of sophisticated methods such as replica exchange molecular dynamics (REMD) and path integral molecular dynamics (PIMD). Inter-atomic forces can be computed by using external codes such as CP2K, Quantum ESPRESSO and LAMMPS.
DCA++ is a software framework to solve correlated electron problems with modern quantum cluster methods. This code provides a state of the art implementation of the dynamical cluster approximation (DCA) and its DCA+ extension. As the cluster solvers, DCA++ provides the continuous-time auxiliary field QMC (CT-AUX) , the continuous-time hybridization expansion (CT-HYB) restricted to single-site problems, the high temperature series expansion (HTS) and the exact diagonalization(ED).
QuCumber is an open-source Python package that implements neural-network quantum state reconstruction of many-body wavefunctions from measurement data such as magnetic spin projections, orbital occupation number. Given a training dataset of measurements, QuCumber discovers the most likely quantum state compatible with the measurements by finding the optimal set of parameters of a restricted Boltzmann machine (RBM).
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w2dynamics is a hybridization-expansion continuous-time (CT-HYB) quantum Monte Carlo package, developed jointly in Wien and Würzburg. Users can calculate local two- and four-pointfermionic Green’s functions of multi-orbital impurity models. This application also provides DMFT Python code and an interface to wannier90 generated Hamiltonians.